Priority junctions should be modelled with same level of detail as signalised junctions.
Intersection geometry and vehicle gap acceptance is used to calculate capacity at priority junctions.
SATURN requires cycle time duration when coding non-signalised junctions. A default parameter (LCY = 75 seconds) will be used if a value is not entered for a particular intersection. It is advised to enter the value for cycle time of the nearest signalised junction, as failure to do so may impact CFPs between adjacent junctions and potentially poor representation of traffic platooning within the network.
In VISUM, the main input for priority ICA calculations is the major flow, i.e. the direction of priority. Major flow is technically defined as a pair of node legs. Care should be taken
when modelling main nodes or nodes with dual-carriageway approaches. As shown in the example within Figure 19, opposing pairs of one way links must be converted to one node leg (by giving them the same orientation) which then allows the major flow to be defined correctly on those node legs.
The ICA calculation of capacity and delays at priority-controlled junctions is primarily based on gap acceptance headways. Critical gap and follow-up gap parameters can be defined by the user or retained as default values provided by HCM. A user-defined override may be required for a roundabout entry as there is no roundabout specific delay model within VISUM. It is advisable that critical gap and follow-up gap values for non-standard priority junctions are estimated within local-scale models such as PICADY and ARCADY (as described in A9.2.2).
6.4.5 Public Transport
Public transport can absorb a proportion of capacity on some network links and turns.
The impact of public transport should be carefully considered, particularly on mixed use links with no dedicated public transport lane.
This section explains how the capacity effect of public transport is addressed within VISUM. The number of bus trips during the assignment period is used as a preload for all turns, and for those links without a bus lane.
In SATURN, a bus-only lane is defined to be a full-length lane from the upstream entry to the downstream stopline. This means bus lanes with set-backs cannot be explicitly modelled within SATURN. This full length lane is used exclusively by any form of public transport being coded as a segregated from general traffic.
In VISUM, the assignment procedure can access several link and turn UDAs which are preset during network coding:
Link UDAs
BUS_LANES: a 0-1 integer attribute which indicates the presence of one or more dedicated bus lanes along the link (1 = present); and
BUS_LOAD: the number of buses that pass along the link during the assignment period.
Turn UDAs
BUS_LOAD: the number of buses that pass along the turn during the assignment period.
It is worth noting that BUS_LOAD has a significant effect on available capacity making it important to specify consistent values for all links. It is advisable to include bus routes with their timetables in the same network model used for road traffic assignment. It is then possible to use analysis functions to count and assign the number of buses within each assignment period for each link or turn.
6.5 Calibration
Calibration of a HTA model involves altering network parameters (e.g. capacities) and travel demand in an attempt to match modelled data (e.g. traffic flows and journey times) to observed data.
This section will not describe the typical parameters used for this exercise (i.e. turn and link counts, journey times and speeds), as the required methodology is not specific to the calibration of HTA models. It is recommended that attention is paid to the location of base data used for calibration and validation to ensure a consistent level of quality across the model study area. One useful approach is to use traffic counts along a series of north-south and east-west screenlines for validation, whilst using counts within the cells formed by those screenlines for calibration purposes.
This subsection will cover some of the more specific capacity calibration exercises used by TD when HTA modelling using VISUM.
VISUM uses the ICA module for capacity and delay calculation. For the ONE model a number of detailed deterministic models (LinSig/TRANSYT) were used to retrieve capacity delay outputs and overwrite the internal ICA calculation. To do this LinSig/
TRANSYT models were coded with identical traffic flow and timing plans as the ONE model. TRANSYT models were also used to indicate the quality of traffic progression between signals. The ICAARRIVALTYPE parameter was adjusted to accommodate the level of progression. The empirical models provided detail about flared approaches.
Capacities were then adjusted according to all the information provided.
Delay and DoS from the local scale models were then compared against ICA output.
VISUM calibration parameters were then adjusted to align ICA junction performance with the local scale modelling. It is advised that a similar approach be adopted for priority junctions. For junctions of this type the VISUM calibration parameters which require adjustment will be the ‘critical gap’ and ‘follow up time’, as these values fundamentally control the time required for an average driver to accept a gap in oncoming flow and merge with traffic.
6.6 Assignment
Route assignment, route choice or traffic assignment relates to the selection of routes (paths) between origins and destinations in transportation networks.
A common assignment procedure within HTA modelling is based on Wardrop’s Principle of Equilibrium66, where travel cost is assumed to depend on the volume of flow in the network. Using this principle, an assumption is made that all drivers have the same perfect knowledge of routes in the network, and that they all seek to minimise the cost of travel without having any preference for the type of road they use (i.e. main or side road). Multiple user class (MUC) assignment can also be used to achieve equilibrium between modelled supply and demand. This is achieved by biasing certain user classes towards longer (rat run) or shorter (sign posted) routes.
66 Wardrop J G, Some theoretical aspects of road traffic research, Proceedings, Institution of Civil Engineers, PART II, Vol.1, 1952, pp325-378.
SATURN can undertake MUC assignment using a similar approach to Wardrop equilibrium. Instead of a single ‘all or nothing’ assignment SATURN completes one assignment for each user class and updates costs after all user classes have been re-assigned. Hence at the end of the algorithm the fraction of trips assigned to each iteration’s routes is identical across all classes. SATURN also contains a Stochastic User Equilibrium (SUE) assignment algorithm, but from a practitioner’s point of view it is advisable to use Wardrop equilibrium assignment within a congested urban network.
PTV AG advocates the use of the Equilibrium Lohse procedure67 within VISUM. The Equilibrium Lohse procedure simulates the learning process of road users using the network. Based on an ‘all or nothing’ assignment, drivers make use of information gained during their previous trip for the new route search. TD believe this is the best methodology for HTA modelling within London using VISUM. This type of assignment was used for the ONE model in combination with Wardrop equilibrium.